一种基于社交网络局部信息的改进社区检测算法

Xiao-Feng Lei, Zhang Lejun, Zhang Jianpei, Yang Jing, Guo Lin
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引用次数: 0

摘要

社区检测是近年来研究的热点问题,本文首先对基于局部信息的相关聚类技术进行了研究和总结。其次,对标签传播算法(简称LPA)进行了深入的研究和分析。最后,针对LPA随机策略导致网络划分总是不最优的问题,引入节点属性相似度的概念,提出基于节点属性相似度的标签传播算法,简称LPA- sna。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Community Detection Algorithm Based on Local Information in Social Networks
As community detection having been a hot issue in recent years, firstly the correlate clustering technologies based on local information are studied and summarized. Secondly, the label propagation algorithm that is short for LPA is researched and analyzed in depth. Finally, for the random strategy of LPA results that the network partition is always not optimal, we introduces the concept of the similarity of nodes' attributes, and proposes label propagation algorithm on the basis of the similarity of nodes' attributes called LPA-SNA for short.
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